import torch

DEVICE = "cuda:3" if torch.cuda.is_available() else "cpu"

LOAD_MODEL = True
SAVE_MODEL = True
BATCH_SIZE = 64
NUM_EPOCHS = 20000
LEARNING_RATE = 5e-5
#source_face = "Leonard"
#source_face = "Cage"
# modify when running train.py
source_face = "Cage"
target_face = "Trump"
# modify when running test.py
mark_ratio = 1.0
train_sourse_face = "Cage"

FACE_A_PATH = "./data/" + source_face
FACE_B_PATH = "./data/" + target_face

TEST_IMG_PATH = "./img"   ####
SAVING_IMG_PATH = "./result/" + source_face + "_" + target_face + ".png"
CHECKPOINT_fake = "./checkpoint/fake_" + source_face + "_" + target_face + ".pth"
CHECKPOINT_discriminator = "./checkpoint/watermark_" + source_face + "_" + target_face + ".pth"

CHECKPOINT_test_watermark = "./checkpoint/watermark_" + train_sourse_face + "_" + target_face + ".pth"
CHECKPOINT_fake_test = "./checkpoint/fake_test_" + source_face + "_" + target_face + ".pth"
CHECKPOINT_discriminator_test = "./checkpoint/discriminator_test_" + source_face + "_" + target_face + ".pth"

CHECKPOINT_discriminator_test_non = "./checkpoint/test_non_d.pth"
CHECKPOINT_fake_test_non = "./checkpoint/test_non_g.pth"
